I accidentally found the paper about mmt [1] [1] : https://ufal.mff.cuni.cz/eamt2017/user-project-product-papers/papers/user/EAMT2017_paper_88.pdf
Il giorno gio 1 dic 2016 alle ore 22:19 Mattmann, Chris A (3010) < chris.a.mattm...@jpl.nasa.gov> ha scritto: > Guys I want to point you at the DARPA D3M program: > > http://www.darpa.mil/program/data-driven-discovery-of-models > > I’m part of the Government Team for the program. This will be a good > connection > to have b/c it’s focused on automatically doing model and code building > for ML based > approaches. > > > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > Chris Mattmann, Ph.D. > Principal Data Scientist, Engineering Administrative Office (3010) > Manager, Open Source Projects Formulation and Development Office (8212) > NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA > Office: 180-503E, Mailstop: 180-503 > Email: chris.a.mattm...@nasa.gov > WWW: http://sunset.usc.edu/~mattmann/ > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > Director, Information Retrieval and Data Science Group (IRDS) > Adjunct Associate Professor, Computer Science Department > University of Southern California, Los Angeles, CA 90089 USA > WWW: http://irds.usc.edu/ > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > > > On 12/1/16, 1:15 PM, "Matt Post" <p...@cs.jhu.edu> wrote: > > John, > > Thanks for sharing, this is really helpful. I didn't realize that > Marcello was involved. > > I think we can identify with the NMT danger. I still think there is a > big niche that deep learning approaches won't reach for a few years, until > GPUs become super prevalent. Which is why I like ModernMT's approaches, > which overlap with many of the things I've been thinking. One thing I > really like is there automatic context-switching approach. This is a great > way to build general-purpose models, and I'd like to mimic it. I have some > general ideas about how this should be implemented but am also looking into > the literature here. > > matt > > > > On Dec 1, 2016, at 1:46 PM, John Hewitt <john...@seas.upenn.edu> > wrote: > > > > I had a few good conversations over dinner with this team at AMTA in > Austin > > in October. > > They seem to be in the interesting position where their work is > good, but > > is in danger of being superseded by neural MT as they come out of > the gate. > > Clearly, it has benefits over NMT, and is easier to adopt, but may > not be > > the winner over the long run. > > > > Here's the link > > < > https://amtaweb.org/wp-content/uploads/2016/11/MMT_Tutorial_FedericoTrombetti_wide-cover.pdf > > > > to their AMTA tutorial. > > > > -John > > > > On Thu, Dec 1, 2016 at 10:17 AM, Mattmann, Chris A (3010) < > > chris.a.mattm...@jpl.nasa.gov> wrote: > > > >> Wow seems like this kind of overlaps with BigTranslate as well.. > thanks > >> for passing > >> along Matt > >> > >> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > >> Chris Mattmann, Ph.D. > >> Principal Data Scientist, Engineering Administrative Office (3010) > >> Manager, Open Source Projects Formulation and Development Office > (8212) > >> NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA > >> Office: 180-503E, Mailstop: 180-503 > >> Email: chris.a.mattm...@nasa.gov > >> WWW: http://sunset.usc.edu/~mattmann/ > >> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > >> Director, Information Retrieval and Data Science Group (IRDS) > >> Adjunct Associate Professor, Computer Science Department > >> University of Southern California, Los Angeles, CA 90089 USA > >> WWW: http://irds.usc.edu/ > >> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > >> > >> > >> On 12/1/16, 4:47 AM, "Matt Post" <p...@cs.jhu.edu> wrote: > >> > >> Just came across this, and it's really cool: > >> > >> https://github.com/ModernMT/MMT > >> > >> See the README for some great use cases. I'm surprised I'd never > heard > >> of this before as it's EU funded and associated with U Edinburgh. > >> > >> > > > >
